The Non-linear Study Of The 12-lead ECG Signal Of The Elderly

The heart is one of the most important organs of human body.The pain and disorder caused by heart disease has become the focus of many countries,and thus has been widely concerned in the world.In recent years,with the improvement of living standards,people pay more attention to the prevention of heart disease.Due to the complex blood vessels and nerve tissues of the heart,the treatment of heart diseases requires high costs.The heart has complex blood vessels and nerve tissue that make the treatment of heart disease costly.In order to prevent the occurrence of heart disease and reveal the relationship between the state and characteristics of the heart system,medical researchers and scientific researchers around the world have invested a lot of research.In the field of biomedical engineering,researchers link ECG signals,autonomic nervous system and physiological state in order to study electrocardiograms.The autonomic nervous system controls the heart to produce electrical signals,and changes in electrical signals will cause changes in physiological states.Traditionally,ecg signal is an objective reflection of physiological state.Because of the guiding significance of ecg signals to the description of physiological state that the study of ecg signals has the most important value.Traditionally,ECG signal is periodic.With the deep research on ECG signal,it is found that the period of ECG signal is changing,not a definite value.Strictly,it does not belong to the definite signal.The analysis of random signal is mainly described by statistics,including histogram,square difference,etc.In the early study of ECG signal,a large number of scholars analyzed the statistical characteristics of ECG signal.With the development of nonlinear science and computer technology,people gradually use theoretical knowledge of other disciplines to study ECG signal.The study of ECG signals is no longer limited to time-frequency domain analysis,but use of nonlinear theory and complexity science is a new perspective on the qualitative interpretation of ECG signals.From the view ofnonlinear science,the 12-lead ECG signal is dissected in this paper,which combines the fractal theory with the trend fluctuation analysis method,and analyzed from another angle by using the complexity algorithm.In this experiment,the ECG signals of ten elderly people in three states were selected,the nonlinear characteristic analysis by using multiple fractal trend fluctuation analysis(MFDFA)method,and respectively researched in myocardial infarction,arrhythmia and normal state.It is found that three kinds of signals have multiple fractal characteristics,and the long-range correlation values of different states are also different.By calculating the Hurst Index,mass index and multifractal spectrum,the analysis shows that three kinds of signals have multifractal characteristics,and three physiological states are easy to distinguish.The waveform of standard 12-lead ecg signal is drawn,and the recognition result is consistent with the fractal theory.Finally,three kinds of state ECG signal LZ complexity are calculated respectively,and the feature recognition of the signal is determined.Based on the characteristics of ECG signals,it is found that some methods in nonlinear science can be used to describe the state of ECG signals and identify different physio-pathology states.This will provide ideas for extensive research of human physiological signals and assist doctors in providing reference for the diagnosis,but also may provide assistance for early diagnosis and treatment of heart patients.